Application Of Deep Learning In Videosecurity Monitoring System

Safe operation is an important part of the healthy development of forest parks and is related to the safety of life and property of each visitor.In recent years,public security and disaster incidents have occurred frequently,and early warning and prevention methods have not been perfected.Early warning and prevention rely on video surveillance,and the means are single.Video surveillance is often used as a basis for post-investigation,and its precautionary ability is weak.The video surveillance coverage is insufficient and there is no comprehensive control.As a public activity space,the park lacks face recognition technology for potential criminals to conduct detailed monitoring and tracking,and fails to achieve high-precision and rapid strikes.Therefore,this thesis proposes to develop an intelligent video surveillance system that supports face recognition technology,timely warning,rapid response,and precision strike to solve the challenges and future development needs of park security work.This thesis gives an overview of the construction background of the forest park video security monitoring system,pointing out that the system development has an important impact on the safe development of the park,and clarifies the purpose and significance of the research.(1)Analysis of the needs of the forest park video security monitoring system,pointing out the overall needs of the system construction,different user function use cases,core business processes,etc.for the park site management personnel,monitoring room monitoring personnel,park supervisors,system administrators,etc.An analysis was conducted to analyze the concepts,applications,and roles of deep learning and intelligent security.(2)The design principles and design ideas of the video security monitoring system are proposed.The system architecture is constructed in general,and the application,technology and network deployment are designed.The system application function composition,development technology and hardware deployment are clarified.Detailed design of the system function structure and the core module setting monitoring screen number,query deletion modification monitoring point,monitoring video playback,etc.The algorithm of deep learning is designed to form the technology and process design of face recognition.The system database was designed by E-R diagram and database table structure.(3)The coding implements the specific functions of the video security monitoring system,implements the training algorithm of the convolutional neural network,and describes the human identification process.The function of deep learning face recognition is realized.The system is tested in terms of function,data integrity and performance.The test results show that the system functions normally and the performance is stable and can be released online.This project develops the video security monitoring system of the forest park,realizes the refined management of the park security,improves the safety emergency command and decision-making ability,realizes the intelligent operation and intelligentizes the daily work,and the application of the system improves the safety management level of the park.Ensure that the park is safe,stable and sustainable.